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      1 /*
      2  * Copyright (C) 2012, 2013 Apple Inc. All rights reserved.
      3  *
      4  * Redistribution and use in source and binary forms, with or without
      5  * modification, are permitted provided that the following conditions
      6  * are met:
      7  * 1. Redistributions of source code must retain the above copyright
      8  *    notice, this list of conditions and the following disclaimer.
      9  * 2. Redistributions in binary form must reproduce the above copyright
     10  *    notice, this list of conditions and the following disclaimer in the
     11  *    documentation and/or other materials provided with the distribution.
     12  *
     13  * THIS SOFTWARE IS PROVIDED BY APPLE INC. AND ITS CONTRIBUTORS ``AS IS''
     14  * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
     15  * THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
     16  * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR ITS CONTRIBUTORS
     17  * BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
     18  * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
     19  * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
     20  * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
     21  * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
     22  * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
     23  * THE POSSIBILITY OF SUCH DAMAGE.
     24  */
     25 
     26 var Statistics = new (function () {
     27 
     28     this.max = function (values) {
     29         return Math.max.apply(Math, values);
     30     }
     31 
     32     this.min = function (values) {
     33         return Math.min.apply(Math, values);
     34     }
     35 
     36     this.sum = function (values) {
     37         return values.reduce(function (a, b) { return a + b; }, 0);
     38     }
     39 
     40     this.squareSum = function (values) {
     41         return values.reduce(function (sum, value) { return sum + value * value;}, 0);
     42     }
     43 
     44     // With sum and sum of squares, we can compute the sample standard deviation in O(1).
     45     // See https://rniwa.com/2012-11-10/sample-standard-deviation-in-terms-of-sum-and-square-sum-of-samples/
     46     this.sampleStandardDeviation = function (numberOfSamples, sum, squareSum) {
     47         if (numberOfSamples < 2)
     48             return 0;
     49         return Math.sqrt(squareSum / (numberOfSamples - 1)
     50             - sum * sum / (numberOfSamples - 1) / numberOfSamples);
     51     }
     52 
     53     this.supportedConfidenceLevels = function () {
     54         var supportedLevels = [];
     55         for (var quantile in tDistributionInverseCDF)
     56             supportedLevels.push((1 - (1 - quantile) * 2).toFixed(2));
     57         return supportedLevels;
     58     }
     59 
     60     // Computes the delta d s.t. (mean - d, mean + d) is the confidence interval with the specified confidence level in O(1).
     61     this.confidenceIntervalDelta = function (confidenceLevel, numberOfSamples, sum, squareSum) {
     62         var probability = (1 - (1 - confidenceLevel) / 2);
     63         if (!(probability in tDistributionInverseCDF)) {
     64             console.warn('We only support ' + this.supportedConfidenceLevels().map(
     65                 function (level) { return level * 100 + '%'; } ).join(', ') + ' confidence intervals.');
     66             return NaN;
     67         }
     68         if (numberOfSamples - 2 < 0)
     69             return NaN;
     70 
     71         var cdfForProbability = tDistributionInverseCDF[probability];
     72         var degreesOfFreedom = numberOfSamples - 1;
     73         if (degreesOfFreedom > cdfForProbability.length) {
     74             console.warn('We only support up to ' + cdfForProbability.length + ' degrees of freedom');
     75             return NaN;
     76         }
     77 
     78         // tDistributionQuantile(degreesOfFreedom, confidenceLevel) * sampleStandardDeviation / sqrt(numberOfSamples) * S/sqrt(numberOfSamples)
     79         var quantile = cdfForProbability[degreesOfFreedom - 1]; // The first entry is for the one degree of freedom.
     80         return quantile * this.sampleStandardDeviation(numberOfSamples, sum, squareSum) / Math.sqrt(numberOfSamples);
     81     }
     82 
     83     this.confidenceInterval = function (values, probability) {
     84         var sum = this.sum(values);
     85         var mean = sum / values.length;
     86         var delta = this.confidenceIntervalDelta(probability || 0.95, values.length, sum, this.squareSum(values));
     87         return [mean - delta, mean + delta];
     88     }
     89 
     90     // See http://en.wikipedia.org/wiki/Student's_t-distribution#Table_of_selected_values
     91     // This table contains one sided (a.k.a. tail) values.
     92     var tDistributionInverseCDF = {
     93         0.9: [
     94             3.077684, 1.885618, 1.637744, 1.533206, 1.475884, 1.439756, 1.414924, 1.396815, 1.383029, 1.372184,
     95             1.363430, 1.356217, 1.350171, 1.345030, 1.340606, 1.336757, 1.333379, 1.330391, 1.327728, 1.325341,
     96             1.323188, 1.321237, 1.319460, 1.317836, 1.316345, 1.314972, 1.313703, 1.312527, 1.311434, 1.310415,
     97             1.309464, 1.308573, 1.307737, 1.306952, 1.306212, 1.305514, 1.304854, 1.304230, 1.303639, 1.303077,
     98             1.302543, 1.302035, 1.301552, 1.301090, 1.300649, 1.300228, 1.299825, 1.299439, 1.299069, 1.298714,
     99 
    100             1.298373, 1.298045, 1.297730, 1.297426, 1.297134, 1.296853, 1.296581, 1.296319, 1.296066, 1.295821,
    101             1.295585, 1.295356, 1.295134, 1.294920, 1.294712, 1.294511, 1.294315, 1.294126, 1.293942, 1.293763,
    102             1.293589, 1.293421, 1.293256, 1.293097, 1.292941, 1.292790, 1.292643, 1.292500, 1.292360, 1.292224,
    103             1.292091, 1.291961, 1.291835, 1.291711, 1.291591, 1.291473, 1.291358, 1.291246, 1.291136, 1.291029,
    104             1.290924, 1.290821, 1.290721, 1.290623, 1.290527, 1.290432, 1.290340, 1.290250, 1.290161, 1.290075],
    105         0.95: [
    106             6.313752, 2.919986, 2.353363, 2.131847, 2.015048, 1.943180, 1.894579, 1.859548, 1.833113, 1.812461,
    107             1.795885, 1.782288, 1.770933, 1.761310, 1.753050, 1.745884, 1.739607, 1.734064, 1.729133, 1.724718,
    108             1.720743, 1.717144, 1.713872, 1.710882, 1.708141, 1.705618, 1.703288, 1.701131, 1.699127, 1.697261,
    109             1.695519, 1.693889, 1.692360, 1.690924, 1.689572, 1.688298, 1.687094, 1.685954, 1.684875, 1.683851,
    110             1.682878, 1.681952, 1.681071, 1.680230, 1.679427, 1.678660, 1.677927, 1.677224, 1.676551, 1.675905,
    111 
    112             1.675285, 1.674689, 1.674116, 1.673565, 1.673034, 1.672522, 1.672029, 1.671553, 1.671093, 1.670649,
    113             1.670219, 1.669804, 1.669402, 1.669013, 1.668636, 1.668271, 1.667916, 1.667572, 1.667239, 1.666914,
    114             1.666600, 1.666294, 1.665996, 1.665707, 1.665425, 1.665151, 1.664885, 1.664625, 1.664371, 1.664125,
    115             1.663884, 1.663649, 1.663420, 1.663197, 1.662978, 1.662765, 1.662557, 1.662354, 1.662155, 1.661961,
    116             1.661771, 1.661585, 1.661404, 1.661226, 1.661052, 1.660881, 1.660715, 1.660551, 1.660391, 1.660234],
    117         0.975: [
    118             12.706205, 4.302653, 3.182446, 2.776445, 2.570582, 2.446912, 2.364624, 2.306004, 2.262157, 2.228139,
    119             2.200985, 2.178813, 2.160369, 2.144787, 2.131450, 2.119905, 2.109816, 2.100922, 2.093024, 2.085963,
    120             2.079614, 2.073873, 2.068658, 2.063899, 2.059539, 2.055529, 2.051831, 2.048407, 2.045230, 2.042272,
    121             2.039513, 2.036933, 2.034515, 2.032245, 2.030108, 2.028094, 2.026192, 2.024394, 2.022691, 2.021075,
    122             2.019541, 2.018082, 2.016692, 2.015368, 2.014103, 2.012896, 2.011741, 2.010635, 2.009575, 2.008559,
    123 
    124             2.007584, 2.006647, 2.005746, 2.004879, 2.004045, 2.003241, 2.002465, 2.001717, 2.000995, 2.000298,
    125             1.999624, 1.998972, 1.998341, 1.997730, 1.997138, 1.996564, 1.996008, 1.995469, 1.994945, 1.994437,
    126             1.993943, 1.993464, 1.992997, 1.992543, 1.992102, 1.991673, 1.991254, 1.990847, 1.990450, 1.990063,
    127             1.989686, 1.989319, 1.988960, 1.988610, 1.988268, 1.987934, 1.987608, 1.987290, 1.986979, 1.986675,
    128             1.986377, 1.986086, 1.985802, 1.985523, 1.985251, 1.984984, 1.984723, 1.984467, 1.984217, 1.983972],
    129         0.99: [
    130             31.820516, 6.964557, 4.540703, 3.746947, 3.364930, 3.142668, 2.997952, 2.896459, 2.821438, 2.763769,
    131             2.718079, 2.680998, 2.650309, 2.624494, 2.602480, 2.583487, 2.566934, 2.552380, 2.539483, 2.527977,
    132             2.517648, 2.508325, 2.499867, 2.492159, 2.485107, 2.478630, 2.472660, 2.467140, 2.462021, 2.457262,
    133             2.452824, 2.448678, 2.444794, 2.441150, 2.437723, 2.434494, 2.431447, 2.428568, 2.425841, 2.423257,
    134             2.420803, 2.418470, 2.416250, 2.414134, 2.412116, 2.410188, 2.408345, 2.406581, 2.404892, 2.403272,
    135 
    136             2.401718, 2.400225, 2.398790, 2.397410, 2.396081, 2.394801, 2.393568, 2.392377, 2.391229, 2.390119,
    137             2.389047, 2.388011, 2.387008, 2.386037, 2.385097, 2.384186, 2.383302, 2.382446, 2.381615, 2.380807,
    138             2.380024, 2.379262, 2.378522, 2.377802, 2.377102, 2.376420, 2.375757, 2.375111, 2.374482, 2.373868,
    139             2.373270, 2.372687, 2.372119, 2.371564, 2.371022, 2.370493, 2.369977, 2.369472, 2.368979, 2.368497,
    140             2.368026, 2.367566, 2.367115, 2.366674, 2.366243, 2.365821, 2.365407, 2.365002, 2.364606, 2.364217]
    141     };
    142 
    143 })();
    144 
    145 if (typeof module != 'undefined') {
    146     for (var key in Statistics)
    147         module.exports[key] = Statistics[key];
    148 }
    149